1. Technical Field
The present invention relates to cleaning path guidance of an automatic cleaning device, and more particularly to a cleaning path guidance method combined with a dirt detection mechanism.
2. Related Art
An automatic cleaning device is generally a dust suction device that has moving power and an obstacle detection function to move by itself in an area to be cleaned, so as to clean the area to be cleaned.
In order to clear thoroughly the area to be cleaned, the automatic cleaning device has one or multiple path guidance mechanisms for guiding the automatic cleaning device along a certain path to clean the area to be cleaned.
The simplest path guidance mechanism is a simple mode-switch guidance mechanism. In the simple mode-switch guidance mechanism, a plurality of cleaning path modes such as a bounce cleaning path mode, a wall follow cleaning path mode, and a Snake cleaning path mode is built in the automatic cleaning device. The automatic cleaning device generally takes a time schedule as a basis for switching. When a specified time point is reached, the automatic cleaning device is switched to a cleaning path mode corresponding to the time point. Through the simple mode-switch guidance mechanism, the automatic cleaning device performs different cleaning path modes and ensures a good cleaning effect for different dirt distribution and dirt levels. However, for a relatively complex indoor environment, for example, a room/house of a particular layout or a house with many obstacles, the simple mode-switch guidance mechanism cannot ensure that the automatic cleaning device can complete the cleaning thoroughly.
For the simple mode-switch guidance mechanism, an improved solution integrated with artificial intelligence (AI) is proposed. In a mode-switch guidance mechanism integrated with AI, the multiple cleaning path modes is still built in the automatic cleaning device, but a dirt detection mechanism is further set in the automatic cleaning device to detect the dirt distribution and the dirt level through various sensors. By analyzing the dirt distribution and the dirt level through AI, the automatic cleaning device can select a cleaning path mode in which the cleaning is most likely completed from multiple cleaning path modes and is switched to the selected cleaning path mode. After being integrated with AI, the cleaning path mode built in the automatic cleaning device is the same as the simple mode-switch guidance mechanism, but the automatic cleaning device can select an optimal cleaning path mode through AI, in order to complete the cleaning fully.
In the two guidance modes, the automatic cleaning device goes forward blindly and changes a travel direction when touching an obstacle or a preset border. In this case, the automatic cleaning device may rarely or even never pass through a specific local block, thus resulting in poor cleaning in the specific local block.
A systematic navigation guidance mechanism is further therefore proposed to integrate a simultaneous localization and mapping (SLAM) algorithm into the automatic cleaning device. The automatic cleaning device makes a map of the area to be cleaned in a cleaning process. The automatic cleaning device plans an optimal cleaning strategy in the area to be cleaned in combination with the dirt detection mechanism, so as to ensure that each corner in the area to be cleaned can really be cleaned.
In theory, the systematic navigation guidance mechanism is an optimal guidance mechanism and is capable of really completing the cleaning, but in practice, due to disadvantages of the detection mechanism and a poor design of a dust suction mechanism, the following problems occur: the specific local block is not really cleaned, the cleaning effect is influenced negatively due to misjudgment of the detection mechanism, and the cleaning time is too long. Planning an optimal cleaning strategy through a detection result of the dirt detection mechanism and a map of areas to be cleaned is therefore still a problem to be solved.